!7165 [MSLITE][Develop] optimize arm fp32 cpu op lstm: add neon

Merge pull request !7165 from yangruoqi713/lite

mindspore/lite/nnacl/fp32/lstm.c

@@ -37,16 +37,44 @@ void MatMulAcc(float *output, const float *input, const float *weight, int rows,
   for (int r = 0; r < rows; r++) {
     for (int c = 0; c < cols; c++) {
       float res = 0;
-      for (int i = 0; i < inner_size; i++) {
-        res += input[r * inner_size + i] * weight[c * inner_size + i];
+      const float *input_col = input + r * inner_size;
+      const float *weight_col = weight + c * inner_size;
+      int index = 0;
+#ifdef ENABLE_ARM
+      float32x4_t out = vdupq_n_f32(0.0f);
+      for (; index < inner_size - 4; index += 4) {
+        float32x4_t in_0 = vld1q_f32(input_col + index);
+        float32x4_t in_1 = vld1q_f32(weight_col + index);
+        out = vmlaq_f32(out, in_1, in_0);
+      }
+#ifdef ENABLE_ARM64
+      res += vaddvq_f32(out);
+#else
+      float32x2_t add2 = vadd_f32(vget_low_f32(out), vget_high_f32(out));
+      float32x2_t add4 = vpadd_f32(add2, add2);
+      res += vget_lane_f32(add4, 0);
+#endif
+#endif
+      for (; index < inner_size; index++) {
+        res += input_col[index] * weight_col[index];
       }
       output[r * cols + c] += res;
     }
   }
 }
 
-void ElementMulAcc(float *input0, float *input1, float *output, int element_size) {
-  for (int index = 0; index < element_size; index++) {
+void ElementMulAcc(const float *input0, const float *input1, float *output, int element_size) {
+  int index = 0;
+#ifdef ENABLE_ARM
+  for (; index < element_size - 4; index += 4) {
+    float32x4_t in_0 = vld1q_f32(input0 + index);
+    float32x4_t in_1 = vld1q_f32(input1 + index);
+    float32x4_t out = vld1q_f32(output + index);
+    out = vmlaq_f32(out, in_1, in_0);
+    vst1q_f32(output + index, out);
+  }
+#endif
+  for (; index < element_size; index++) {
     output[index] += input0[index] * input1[index];
   }
 }

mindspore/lite/src/ops/constant_of_shape.cc

@@ -67,7 +67,11 @@ int ConstantOfShape::InferShape(std::vector<Tensor *> inputs_, std::vector<Tenso
   if (!GetInferFlag()) {
     return RET_OK;
   }
-  auto in_data = reinterpret_cast<int *>(in_tensor->MutableData());
+  auto in_data = reinterpret_cast<int *>(in_tensor->data_c());
+  if (in_data == nullptr) {
+    MS_LOG(ERROR) << "Input data is nullptr";
+    return RET_INFER_INVALID;
+  }
   int size = in_tensor->ElementsNum();
   std::vector<int> out_shape(size);
   for (int i = 0; i < size; ++i) {

mindspore/lite/src/ops/lstm.cc

@@ -51,7 +51,7 @@ int Lstm::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
   }
   auto input = inputs_.front();
   MS_ASSERT(input != nullptr);
-  auto weight_i = inputs_.front();
+  auto weight_i = inputs_[1];
   MS_ASSERT(input0 != nullptr);
   auto output = outputs_.front();
   MS_ASSERT(output != nullptr);